Author(s): Shen J, Wang A, Wang Q, Gurvich I, Siegel AB,
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Abstract BACKGROUND: MicroRNAs (miRNA) are abundant in the circulation and play a central role in diverse biologic processes; they may be useful for early diagnosis of hepatocellular carcinoma. METHODS: We conducted a two-phase, case-control study (20 pairs for the discovery set and 49 pairs for the validation set) to test the hypothesis that genome-wide dysregulation of circulating miRNAs differentiates hepatocellular carcinoma cases from controls. Taqman low-density arrays were used to examine genome-wide miRNA expression for the discovery set, and quantitative real-time PCR was used to validate candidate miRNAs for both discovery and validation sets. RESULTS: Sixty-six miRNAs were found to be significantly overexpressed in plasma of hepatocellular carcinoma cases compared with controls after adjusting for false discovery rate (P < 0.05). A volcano plot indicated that seven miRNAs had greater than 2-fold case-control differences with P < 0.01. Four significant miRNAs (miR-150, miR-30c, miR-483-5p, and miR-520b) detectable in all samples with varied expression levels were further validated in a validation set. MiR-483-5p was statistically significantly overexpressed in hepatocellular carcinoma cases compared with controls (3.20 vs. 0.82, P < 0.0001). Hepatocellular carcinoma risk factors and clinic-pathological characteristics did not influence miR-483-5p expression. The combination of plasma miR-483-5p level and hepatitis C virus status can significantly differentiate hepatocellular carcinoma cases from controls with an area under the curve of 0.908 (P < 0.0001). The sensitivity and specificity were, respectively, 75.5\% and 89.8\%. CONCLUSIONS: These preliminary results suggest the importance of dysregulated circulating miR-483-5p as a potential hepatocellular carcinoma biomarker. IMPACT: Confirmation of aberrant expression of miR-483-5p in a large prospective hepatocellular carcinoma study will provide support for its application to hepatocellular carcinoma detection. ©2013 AACR.
This article was published in Cancer Epidemiol Biomarkers Prev
and referenced in Molecular Biology: Open Access